code: def test_keras_convert_sequential():
      # necessary to keep the names of the layers consistent
      K.clear_session()
  
      model = Sequential()
      model.add(Dense(4, input_shape=(3,)))
      model.add(Dense(5))
      model.add(Dense(6))
      wandb_model = wandb.data_types.Graph.from_keras(model)
      wandb_model_out = wandb.Graph._to_graph_json(wandb_model)
      print(wandb_model_out)
      assert wandb_model_out == {
          "format": "keras",
          "nodes": [
              {
                  "name": "dense_input",
                  "id": "dense_input",
                  "class_name": "InputLayer",
                  "output_shape": [(None, 3)],
                  "num_parameters": 0,
              },
              {
                  "name": "dense",
                  "id": "dense",
                  "class_name": "Dense",
                  "output_shape": (None, 4),
                  "num_parameters": 16,
              },
              {
                  "name": "dense_1",
                  "id": "dense_1",
                  "class_name": "Dense",
                  "output_shape": (None, 5),
                  "num_parameters": 25,
              },
              {
                  "name": "dense_2",
                  "id": "dense_2",
                  "class_name": "Dense",
                  "output_shape": (None, 6),
                  "num_parameters": 36,
              },
          ],
          "edges": [
              ["dense_input", "dense"],
              ["dense", "dense_1"],
              ["dense_1", "dense_2"],
          ],
      }
  
file_path: wandb/tests/pytest_tests/unit_tests/test_keras.py
imports: import sys
  import pytest
  import wandb
  from keras import backend
  from keras.layers import LSTM, Concatenate, Dense, Embedding, Flatten, Input
  from keras.models import Model, Sequential
  from wandb.keras import WandbCallback
label_desc: Use image node_id 3 for calling a global function with example usage: test_keras_convert_sequential() without return types